Triple

T2837467
Position Surface form Disambiguated ID Type / Status
Subject İZBAN E62384 entity
Predicate regionServed P82 FINISHED
Object Bayraklı E313198 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Bayraklı | Statement: [İZBAN, regionServed, Bayraklı]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayraklı
Context triple: [İZBAN, regionServed, Bayraklı]
  • A. Bayraklı chosen
    Bayraklı is a coastal district of İzmir, Turkey, known for its modern business centers, residential areas, and proximity to the city’s central urban core.
  • B. Çekmeköy
    Çekmeköy is a residential district on the Asian side of Istanbul, known for its rapidly developing housing areas and proximity to forested green spaces.
  • C. Beykoz
    Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
  • D. Sarıyer
    Sarıyer is a district on the European side of Istanbul, Turkey, known for its Bosphorus coastline, historic neighborhoods, and prominent sports and educational institutions.
  • E. Kadıköy
    Kadıköy is a historic district on the Asian side of Istanbul, Turkey, known for its ancient roots (including the site of the Council of Chalcedon), vibrant cultural life, and bustling waterfront.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdeede0488190a9782f55b57559ee completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1de87779c8190ae6833b80d34f5b2 completed March 11, 2026, 9:28 p.m.
Created at: March 6, 2026, 10:01 p.m.